In recent years, in companies that manage a call center and hold a large volume of voice data, it has been demanded to automate the operation of extracting information from voice data. In particular, a supervisor who manages operators in a call center aims at efficiently finding and checking problematic calls (i.e., complaints) from among a large volume of call voice data, and utilizing the results to educate the operators and promptly deal with the complaints.
As a method for efficiently finding and checking problematic calls, there are known a method for identifying a complaint from a recorded call and a method for identifying a necessary part from which particular information is to be got from a recorded call.
As a method for identifying a complaint from a recorded call, there is known a method of, as shown in Patent Literature 1, for example, converting an emotional expression of a speaker into a feature quantity based on the voice intonation, a change in the voice intensity, and pauses in the recorded voice data, which has been obtained by recording a telephone conversation between a user and an operator, and scoring the voice data using a keyword contained in the voice data as well as the feature quantity that is based on the emotional expression, and then determining which call should be dealt with as a complaint based on the score value.
Meanwhile, as a method for identifying a necessary part from which particular information is to be got from a recorded call, there is known a method of, as shown in Patent Literature 2, for example, identifying a part of the conversation at a point where the speaker changed from an operator to a customer as the necessary part from which particular information is to be got, using a speech time as a parameter, and determining the part as the playback start point (i.e., part-to-elicit).